4627 results about "Biologic marker" patented technology

A federated distributed computational system enables secure oncological therapy optimization through robotic integration. The system establishes a distributed graph architecture with secure communication channels connecting computational nodes, implementing encryption protocols for cross-institutional data exchange. Each node contains processing capabilities for fluorescence-guided imaging, uncertainty quantification, and expert knowledge integration while maintaining hierarchical knowledge graphs of oncological biomarkers, interventions, and outcomes. The system coordinates domain-specific knowledge through token-space communication and implements an advanced robotic integration system for surgical interventions using spatiotemporal tumor mapping, multi-modal fluorescence imaging, surgical robot coordination, and space-time stabilized mesh management. Key capabilities include wavelength-specific multi-modal fluorescence detection, combined epistemic and aleatoric uncertainty estimation, tensor-based data integration with adaptive dimensionality control, and light cone search for adaptive treatment optimization—all while maintaining strict privacy controls.

The invention provides a technical condition prediction method for a tunnel civil engineering structure, and relates to the technical field of traffic control monitoring systems.A biological acoustic composite sensing system comprising a distributed optical fiber acoustic sensing system and microorganism sample collection and analysis is constructed, and acoustic depth mode characteristics are mined by applying a deep learning model; the microbial dynamic biomarker is analyzed and identified by using bioinformatics; multi-modal information, a domain knowledge graph and a causal inference algorithm are fused, and a dynamic causal network model for revealing an internal driving relation in the degradation process is constructed; further, training and applying an adaptive neural network prediction model based on causal driving and fusing physical and biochemical mechanism constraints, and carrying out probabilistic prediction on future technical conditions of the tunnel; and executing anti-fact reasoning by using the causal network and the prediction model, and generating and optimizing an intervention strategy of cooperation of physical measures and biochemical measures. According to the method, the accuracy and advance of tunnel structure state prediction can be remarkably improved.

The invention discloses a breast cancer immunohistochemical index and typing prediction method and system. The prediction method comprises the following steps: acquiring a breast ultrasound image and a breast magnetic resonance image of a patient; performing preprocessing and quality control on the mammary gland ultrasonic image and the mammary gland magnetic resonance image; performing breast lesion area segmentation by adopting a deep learning model to obtain segmented lesion areas; based on the segmented lesion area, extracting multi-modal radiomics characteristics of the breast ultrasonic image and the breast magnetic resonance image; fusing the multi-modal radiomics characteristics of the breast ultrasound image and the breast magnetic resonance image, constructing a machine learning model, and performing immunohistochemical index prediction to obtain an immunohistochemical index prediction result; and performing breast cancer molecular typing analysis according to the immunohistochemical index prediction result. By fusing the multi-modal image information, the tumor features can be described more comprehensively, and the accuracy of biomarker prediction is improved.

The invention relates to the technical field of biomarkers, in particular to a blood biomarker combination for prediction and auxiliary diagnosis of ovarian reserve hypofunction (DOR), a corresponding detection kit and application of the blood biomarker combination. According to the invention, the content change of the nicotinamide mononucleotide (NMN) and the metabolite combination thereof in serum or plasma is screened for the first time and can be used as a detection index for predicting the ovarian reserve function decline. Based on the biomarker combination, the invention further provides an in-vitro detection kit containing a related standard substance, an internal standard solution and an extracting solution, and a data analysis method combined with a random forest model, so that an individual with a normal ovarian reserve function and an individual with hypofunction can be accurately distinguished. The method is noninvasive, simple, convenient, high in sensitivity and suitable for early recognition and layered screening of clinical ovarian reserve hypofunction.

The invention discloses an enteritis patient condition severity risk early warning method, a medium and equipment. The method comprises the following steps: acquiring a borborygmus original signal and a clinical multi-dimensional physiological parameter sequence through a sensing device; constructing a borborygmus dynamic characteristic spectrum based on the borborygmus original signal to generate an acoustic biomarker time sequence; inputting the acoustic biomarker time sequence and the clinical multi-dimensional physiological parameter sequence into a multi-modal fusion early warning model to obtain an intestinal inflammation risk index; executing a signal quality self-evaluation process and generating a data quality warning code when the signal quality is abnormal; triggering a multi-node collaborative monitoring mechanism based on the risk index to generate an intestinal state multi-dimensional situation map; establishing an individualized risk baseline and generating a graded early warning instruction; and finally outputting a comprehensive early warning report. According to the method, multi-modal fusion analysis of the borborygmus signal and the clinical parameters is realized, the accuracy and timeliness of illness state early warning are remarkably improved through dynamic risk assessment and signal quality monitoring, and a reliable basis is provided for clinical decision making.

Provided herein are methods and systems for diagnosing pathological conditions using machine learning and artificial intelligence models. An exemplary method can include loading an abundance matrix that represents mass spectrometry reads of a sample of a plurality of volatile organic compounds (VOCs) extracted from a biological sample. The abundance matrix can represent each of the plurality of VOCs in a mass-to-charge ratio dimension, an abundance dimension, and a retention time dimension. The method can include providing the abundance matrix to a machine-learning model. The machine- learning model can be trained on abundance matrixes of biomarkers of VOCs collected from healthy and diseased subjects. The method can include receiving, from the machine-learning model, a prediction of a state of a disease state.

The disclosure provides technologies that permit detection and / or characterization of brain biomarkers (e.g., disease-associated biomarkers) in non-CNS samples, including by liquid biopsy (e.g., blood, serum, etc.). Among other things, the present disclosure demonstrates that ultrasound opening of the blood brain barrier can achieve detectable increases in brain-derived materials (e.g., brain-derived proteins, neuron-derived extracellular vesicles, and / or cell-free DNA) in readily-sampled systemic liquids.

The invention relates to the technical field of biological medicine, and discloses a pharmaceutical composition of paclitaxel dimer prodrug nanoparticles and a traditional Chinese medicine compound and application of the pharmaceutical composition, and the pharmaceutical composition is composed of Qiyuansanlong prescription freeze-dried powder and paclitaxel dimer prodrug nanoparticles; wherein the paclitaxel dimer prodrug nanoparticles comprise one of NQO1 response type PTX dimer prodrug nanoparticles (PTX-Q-PTX NPs) or GSH (glutathione) response type PTX dimer prodrug nanoparticles (PTX-SeSe-PTXNPs), and the paclitaxel dimer prodrug nanoparticles comprise one of NQO1 response type PTX dimer prodrug nanoparticles (PTX-Q-PTX NPs) and GSH response type PTX dimer prodrug nanoparticles (PTX-SeSe-PTXNPs). According to the pharmaceutical composition disclosed by the invention, a traditional Chinese and western medicine synergistic treatment system is innovatively constructed, and the advantage of multi-dimensional synergistic interaction is shown. Firstly, an NQO1 / GSH double-response type intelligent release system is adopted, and a biomarker highly expressed by tumor tissue can be specifically responded to realize precise drug release, so that the PTX concentration in tumors is improved compared with that of a traditional dosage form, and meanwhile, the drug circulation time is prolonged. Secondly, the active ingredients in the Qiyuansanlong prescription freeze-dried powder can significantly down-regulate the PD-L1 expression level, synergistically enhance CD4 + T and CD8 + T cell infiltration, and form chemical-immune dual killing effects.

The invention discloses a pain management method based on bioelectrical impedance data and a machine learning algorithm, and relates to the technical field of medical health, and the method comprises the steps: carrying out the phase delay analysis of an impedance phase spectrum matrix, calculating the change rate of a phase angle of each frequency point along with time, and obtaining the maximum phase lag time; according to the temperature field sequence and the maximum phase lag time, time-space registration is carried out through a multi-modal data fusion method and impedance modulus changes of the corresponding areas, and a pain biomarker feature library is generated; through a bidirectional LSTM and a cross attention fusion method, time sequence modeling and cross-modal correlation analysis are carried out on bioelectricity signal characteristics extracted by a sliding window and historical pain data, a dynamic evolution rule of pain development is captured, a pain management triple containing pain intensity, intervention response and prognosis evaluation is generated, and a pain management result is obtained. And a quantitative basis is provided for personalized treatment.

The invention provides a hematologic tumor cord blood transplantation treatment prognosis risk assessment method and system based on multi-modal data fusion, a medium and electronic equipment, and relates to the technical field of medical artificial intelligence and clinical decision support systems. The method comprises the following steps: acquiring multi-modal data including unit characteristic data of cord blood of a patient, biomarker data and the like; screening out a simplified feature set from the preprocessed multi-modal data; fusing the simplified features based on three complementary strategies of feature level direct cascade, knowledge graph semantic association and multi-model decision integration; and a prediction model is constructed, and a standardized risk assessment report is generated based on the optimized hierarchical risk levels and is used for assisting clinical decision support. According to the method, accurate layering of the prognosis risk of the hematologic tumor umbilical cord blood transplantation patient is achieved, high-accuracy risk prediction is provided, good interpretability and personalized decision support capacity are achieved, and a scientific basis is provided for clinical practice.

The invention relates to the technical field of health risk assessment, in particular to an intelligent early warning system for postoperative infection risk of orthopedic trauma. The system comprises a data acquisition module for acquiring physiological feature data and biomarker data; the key monitoring and screening module screens key monitoring patients according to the continuous abnormal representation growth degree of the initial physiological signs; the infection risk assessment module obtains a marker level index by using the initial deviation level and the growth amplitude of the biomarker, and obtains a wound infection risk coefficient in combination with the prediction condition of historical biomarker data; and the early warning report generation module is used for dividing patient early warning levels according to the physiological parameter abnormality and the wound infection risk coefficient to generate a risk report. According to the method, the evaluation accuracy of postoperative infection is improved through the physiological sign abnormity continuity and the biomarker sudden increase and prediction trend, the subsequent early warning level and risk report generation are more reliable, and a more personalized and accurate treatment scheme can be provided for a patient.

The invention relates to a breast cancer plasma transporter miRNA marker and application thereof, and belongs to the technical field of biological detection. In the prior art, biomarkers for breast cancer liquid biopsy have the problems of low content, high heterogeneity, insufficient time resolution and the like, so that the detection reliability is limited. According to the invention, a specific miRNA (micro Ribonucleic Acid) marker (including one or more of let-7d-5p, miR-103a-3p and miR-22-3p) of the plasma transporter is provided. The marker can be used for preparing a breast cancer detection reagent or kit. Clinical verifications show that the miRNAs are remarkably and highly expressed in plasma migrators of breast cancer patients, the AUC value reaches 0.763-0.808, the sensitivity is 66.7%-86.7%, the specificity is 66.7%-88.3%, the miRNAs have the advantages of high signal-to-noise ratio and dynamic monitoring, and the accuracy and practicability of breast cancer detection are remarkably improved.

The invention belongs to the technical field of biological medicines, and particularly relates to application of secretory lactase-like protein (LCTL) as a diagnostic marker in preparation of a diagnostic kit for chronic kidney diseases. According to the present invention, the secretory form of the LCTL is found for the first time, the secretory LCTL content in the human serum is detected by using the existing commercial ELISA kit for the first time, and the further research finds that the secretory LCTL content in the serum of the chronic kidney disease patient is significantly reduced compared with the normal person; and the content of the LCTL in the serum is obviously related to the renal function impairment degree and proteinuria degree of the patient, so that the application of the secretory LCTL in preparing the biomarker for diagnosing the chronic kidney disease is provided for the first time. The invention provides a new method for chronic kidney disease diagnosis, and has important clinical significance and commercial value.

The invention discloses a bacterial polypeptide Gfo and application thereof in preparation of rheumatoid arthritis diagnosis products, and belongs to the technical field of rheumatoid arthritis diagnosis. The amino acid sequence of the bacterial polypeptide Gfo is LNSHGFLPETE. A diagnostic product prepared from the bacterial polypeptide Gfo can effectively detect that the level of an anti-bacterial polypeptide Gfo antibody in a biological sample of a rheumatoid arthritis patient is obviously higher than that of healthy people and other rheumatoid immune diseases similar to rheumatoid arthritis. In addition, in CCP antibody and RF negative patients, the increase is still significant. Therefore, the antibacterial polypeptide Gfo antibody is an important biomarker of rheumatoid arthritis, and provides an effective new method for diagnosis of RA, especially diagnosis of serum-negative RA.

The invention discloses a biomarker combination for predicting calendar age, a model and application of the biomarker combination. 57 kinds of DNA methylated CpG sites screened from many elderly subjects are creatively introduced, through multiple detection and large-scale parallel DNA sequencing, operation is easy, the result is highly repeatable, and the age prediction model constructed based on the method is good in stability and accuracy and high in sensitivity and has good application prospects. Calendar age can be predicted from trace blood samples associated with forensic cases.

The invention relates to the technical field of intelligent diagnosis systems for neurodegenerative diseases, and discloses a system and equipment for identifying an early biomarker of Parkinson's disease based on non-invasive electroencephalogram. The Parkinson's disease early-stage biomarker identification system comprises a multi-mode signal acquisition module which is provided with a 64-lead dry electrode electroencephalogram cap, an integrated preamplifier and an ADC converter and is used for synchronously acquiring resting-state electroencephalogram and event-related potential, dynamically completing switching of the resting-state electroencephalogram sampling rate and transmitting acquired original data to a preprocessing module. According to the method, revolutionary improvement is realized in three dimensions of acquisition, analysis and calculation through system-level collaborative innovation, a nanocrystalline shielding dry electrode is combined with a dynamic impedance adjustment technology, so that the signal-to-noise ratio of a home environment is increased to 28dB, and the pathological correlation of key markers such as frontal lobe-basal node loop gamma entropy is verified by Granger causality and has a good application prospect. The cloud distributed model server supports 2000 paths of concurrent analysis, and the real-time bottleneck of home screening is thoroughly solved.

A mask-based diagnostic apparatus is provided for detecting a biomarker contained in exhaled breath of a test subject. An exhaled breath condensate (EBC) collector converts breath vapor received from the lungs and airways of the test subject into a fluid biosample. The EBC collector including a thermal mass, a condensate-forming surface and a fluid conductor disposed on the condensate-forming surface. A fluid transfer system receives the fluid biosample from the EBC collector. A biomarker testing unit receives the fluid biosample from the fluid transfer system and tests the fluid biosample for a target biomarker. A testing system support is provided for supporting the EBC collector, the fluid transfer system and the biomarker testing unit. The testing system support is configured and dimensioned to fit inside a face mask. A face mask is provided forming an exhaled breath vapor containment volume to hold the exhaled breath vapor in proximity to the EBC collector to enable the condensate-forming surface cooled by the thermal mass to coalesce the exhaled breath vapor into the fluid biosample.

The invention discloses an Alzheimer disease risk prediction method based on feature fusion, a medium and equipment. The method comprises the following steps: firstly, acquiring an sMRI image, an FDG-PET image, a biomarker and intelligence score data of a target subject; then, sMRI and FDG-PET image data are respectively input into a three-dimensional convolutional neural network module, and a corresponding first image feature map and a corresponding second image feature map are extracted; secondly, inputting the two feature maps into a cross attention fusion module to obtain image fusion features; and inputting a U-shaped up-sampling network to segment a hippocampus region to obtain hippocampus features. And then, merging the image fusion features, the hippocampus features, the biomarker data and the intelligence score data, and inputting the merged data into an extreme learning machine for calculation, thereby obtaining an onset risk prediction result of the Alzheimer's disease. According to the method, by means of cross-modal data fusion, multi-modal data complementary information is extracted, and the accuracy of onset risk prediction can be effectively improved.

The invention relates to the technical field of molecular markers, in particular to a biomarker related to the zeaxanthin content character of sweet corn kernels and application of the biomarker. The RIL population is used for performing QTL positioning on the corn kernel zeaxanthin content character, it is found that a major QTL related to the sweet corn kernel zeaxanthin content exists on the sixth chromosome of corn, the major QTL is located between SNP sites Schr6: 83027949 and Schr6: 84835891, the phenotype contribution rate of the corn kernel zeaxanthin content is 18.69%, and the major QTL is a major QTL related to the sweet corn kernel zeaxanthin content. The major QTL can be used for screening or auxiliary screening of sweet corn with relatively high zeaxanthin content, when the genotype of Schr6: 83027949 is GG and the genotype of Schr6: 84835891 is AA, the zeaxanthin content is relatively high, technical support is provided for molecular marker-assisted breeding, and the major QTL has important significance in improving the nutritional quality of the sweet corn.

The invention discloses a lung injury evaluation system based on a vascular endothelial cell protection effect, and the system comprises a sample processing module which is configured to execute sample preprocessing and multi-dimensional biomarker collection operation; the feature calculation module is connected to the sample processing module and is configured to perform endothelial function core index quantification and feature extraction operation; the data fusion module is connected to the feature calculation module and is configured to execute lung injury degree and endothelial protection efficiency association mapping operation; and the strategy generation module is connected to the data fusion module and is configured to execute a dynamic risk assessment and assessment strategy generation stage. The method has the following advantages and effects: systematic fusion and dynamic analysis of multi-source heterogeneous data are realized, and quantitative association mapping between biomarkers and iconography features is established, so that the comprehensiveness and predictive ability of state evaluation are remarkably improved.

The present invention discloses a combination of different nucleic acid aptamers with 291 known targets. By performing sequencing analysis on the nucleic acid aptamer sequences of this combination through single-cell high-throughput sequencing technology, a cell atlas targeting mononuclear cells derived from the peripheral blood of patients with cholangiocarcinoma can be constructed. The nucleic acid aptamers covered by this combination have high specific affinity for their molecular targets. After extending adapters commercialized for sequencing platforms at both ends of the nucleic acid aptamer sequences respectively, by performing high-throughput sequencing on the nucleic acid aptamer sequences with sequencing adapters bound to the surface of mononuclear cells, high-throughput analysis of biomarkers on the surface of mononuclear cells derived from the peripheral blood of patients with cholangiocarcinoma can be achieved, thereby constructing a cell atlas of mononuclear cells derived from the peripheral blood of cholangiocarcinoma.

The invention relates to the field of clinical diagnostics, and discloses an elderly NSC emergency risk layering method and device and a medium, and the method comprises the steps: S1, obtaining multi-dimensional evaluation data of an elderly NSC patient; s2, adopting a preset risk mapping rule to convert the risk values into single risk values of a unified scale; s3, dividing the single risk value into a plurality of risk sub-models, and calculating a dimension risk score of each risk sub-model; s4, based on a preset fusion strategy, integrating the risk sub-model and the single risk value interaction effect, and calculating to obtain a total risk score of the patient; and S5, determining the risk level of the patient according to the total risk score, and outputting a clinical diagnosis and treatment suggestion. According to the method, multiple biomarkers and key clinical parameters are integrated, a multi-dimensional combined risk assessment model is constructed, and the potential pathological state of a patient can be reflected more comprehensively.

The invention discloses application of an lncRNA biomarker in esophageal squamous cell carcinoma diagnosis, and relates to the technical field of esophageal squamous cell carcinoma diagnosis. The esophageal squamous cell carcinoma marker comprises LINC00482. The lncRNA marker screened by the invention has the technical advantages of high esophageal squamous cell carcinoma diagnosis sensitivity and strong specificity, has good diagnosis characteristics, and has important significance on early diagnosis, early intervention, deep understanding of the pathological mechanism of esophageal squamous cell carcinoma and the like. In addition, the method for auxiliary diagnosis or diagnosis of esophageal squamous cell carcinoma by using the biomarker has the technical advantages of simple operation, low price and short detection period, and can meet the detection requirements of various samples such as blood, tissues and the like.

The invention relates to a method for acquiring a biomarker for assisting CRLM early diagnosis. The method comprises the following steps: acquiring sequencing data, clinical information and metabonomics characteristics of a CRC sample; evaluating and determining a plurality of differentiated machine learning models; performing classification according to the determined machine learning model, and constructing a CRLM biomarker prediction model; screening candidate biomarkers according to the prediction model; and verifying the candidate biomarker at least according to the tissue slice and the serum sample, and determining a final biomarker.

A mask-based diagnostic apparatus is provided for detecting a biomarker contained in exhaled breath of a test subject. An exhaled breath condensate (EBC) collector converts breath vapor received from the lungs and airways of the test subject into a fluid biosample. The EBC collector including a thermal mass, a condensate-forming surface and a fluid conductor disposed on the condensate-forming surface. A fluid transfer system receives the fluid biosample from the EBC collector. A biomarker testing unit receives the fluid biosample from the fluid transfer system and tests the fluid biosample for a target biomarker. A testing system support is provided for supporting the EBC collector, the fluid transfer system and the biomarker testing unit. The testing system support is configured and dimensioned to fit inside a face mask. A face mask is provided forming an exhaled breath vapor containment volume to hold the exhaled breath vapor in proximity to the EBC collector to enable the condensate-forming surface cooled by the thermal mass to coalesce the exhaled breath vapor into the fluid biosample.

The invention discloses a biomarker for evaluating litchi quality and a detection method, and relates to the technical field of biology. The marker is an SNP (Single Nucleotide Polymorphism) molecular marker, and the nucleotide sequence of the marker is as shown in SEQ ID NO.1-3. The molecular marker disclosed by the invention can be used for evaluating the quality of litchis, particularly evaluating the fructose content. Meanwhile, when the gene is applied to molecular marker assisted selection (MAS) and genome selection (GS), the genetic improvement progress of the litchi variety can be accelerated.

The disclosure relates to methods, compositions, and combinations for detoxification in a patient comprising performing therapeutic plasma exchange (TPE) on the patient. The disclosure also relates to methods, compositions, and combinations for removing toxins in a patient as a result of chronic exposure to the toxins, comprising performing one or more TPE sessions on the patient and administering an oral composition to the patient. The methods, compositions, and combinations of the disclosure may also be used to replenish biomarkers indicative of a healthy state of the body in order to improve immune system function or patient longevity, and / or reduce oxidative stress or inflammation. The methods, compositions, and combinations of the disclosure may also be used to reduce the level of atherosclerosis, improve cognitive function, prevent early cancer development, promote immune health, and / or treat health conditions or diseases such as autoimmune diseases, cancers, Alzheimer's disease, Parkinson's disease, chronic fatigue syndromes, or fibromyalgia. Additionally, the methods, compositions, and combinations of the disclosure may comprise an intravenous supplementation, wherein each TPE session is followed by administration to the patient of an IV composition. The disclosure further relates to oral compositions and IV compositions for use in the methods, compositions, and combinations of the disclosure.

The invention provides a screening method and application of an early prediction marker of papillary thyroid cancer, the early prediction marker of papillary thyroid cancer is P4HA2, application of a reagent for detecting the expression level of P4HA2 in preparation of a product is provided, and a P4HA2 inhibitor including a substance for knocking down P4HA2 gene expression is also provided. The invention also provides application of the P4HA2 inhibitor in preparation of a product for inhibiting migration and / or proliferation of thyroid cancer cells, and a screening method of a biomarker for predicting papillary thyroid cancer. The marker can be used for prediction and early prediction of papillary thyroid cancer, knock-down of the marker can also be used for prediction and early prediction of papillary thyroid cancer, early screening can be better completed, benign and malignant nodules are helped to be distinguished, unnecessary invasive detection is reduced, and the detection efficiency is improved. And a new view angle is provided for molecular mechanism research and early diagnosis of thyroid cancer.

The invention provides an immunotherapy reaction marker identification method and system based on a cooperative game theory, and relates to the technical field of intelligent medical treatment, and the method comprises the following steps: obtaining immunotherapy single cell sequencing data, and determining a candidate gene set through differential expression analysis; extracting regulation and control relation pairs of the candidate gene set to obtain a multi-level information gene regulation and control network; embedding the multilevel information gene regulation and control network by adopting a Node2vec algorithm to obtain a network module containing potential biological functions, calculating the contribution degree of each gene feature to model prediction based on a Myerson value, and obtaining a feature importance sequence; combining the optimal features of the modules into a global candidate set; and iteratively optimizing the global candidate set, and outputting a target immunotherapy reaction marker set. Through a Myerson value principle in a cooperative game, a biomarker set related to immunotherapy response is efficiently searched, deep analysis of a drug resistance mechanism is realized, the accuracy and robustness of marker screening are improved, and the method serves for cancer clinical scheme customization.

The invention discloses a sweat uric acid and glucose sensor based on a carbon nanotube (CNT) enhanced electrochemical platform, and aims to solve the sensitivity challenge of low-concentration biomarker detection in sweat. The enzyme is covalently immobilized on the CNT through an EDC / NHS chemical method, so that the catalytic efficiency, the electron transfer speed and the sensor stability are remarkably improved, and the ultralow detection lower limit of uric acid and glucose is realized. According to the device, uric acid, glucose and pH sensing functions are integrated on a single wearable platform, efficient flowing and rapid updating of sweat are ensured through a radiation symmetry microfluid design optimized through finite element analysis, and real-time biomarker monitoring is supported. The material innovation (such as CNT-enzyme complex) and fluid dynamics optimization of the invention overcome the key problem in the field of wearable biosensing, and provide an extensible solution for the next generation of non-invasive health monitoring.